{"title":"Active Distribution System State Estimation: Comparison Between Weighted Least Squares and Extended Kalman Filter Algorithms","authors":"J. Watitwa, K. Awodele","doi":"10.1109/PowerAfrica49420.2020.9219899","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219899","url":null,"abstract":"Power distribution systems have a topology which is typically unknown to the distribution system operators. Remote Terminal Units and SCADAs monitor these networks primarily at the substation level. However, with the widespread integration of Distributed Generation units (DGs), the need for real-time control of Active Distribution Networks is urgent. While DGs can improve the performance of power systems through voltage support, price elasticity, and reduced emissions of greenhouse gases, they also present challenges such as voltage spikes and bidirectional power flows. The distribution systems' state needs to be known accurately with high refresh rates and low time latency to deal with these issues. Real-time state estimation (SE) that use of Phasor Measurement Units (PMU) data allows the prediction of the distribution systems' nodal voltages and phasor angles. This paper presents a performance analysis comparison between the Weighted Least Square (WLS) and the Extended Kalman Filter (EKF) algorithms on active distribution grids. The WLS is a static SE algorithm, while EKF is a recursive SE method. The paper first recounts the analytical formulation of both approaches and then quantifies the differences in their performance. The tests were carried out on a modified IEEE-33 bus test feeder that included an optimally placed DG. For the test feeder's nodes load profile, the PMU-data generated during the ADRES-CONCEPT project was used. MATLAB and OpenDSS software were used to run the experiments. The results show that if the process model is correct, the EKF approach performs better.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123820188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, E. Frimpong
{"title":"Adaptive PI-GA Based Technique for Automatic Generation Control with Renewable Energy Integration","authors":"Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, E. Frimpong","doi":"10.1109/PowerAfrica49420.2020.9219960","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219960","url":null,"abstract":"To enhance the reliability of the power system, conventional power grid requires a robust automatic generation control system to maintain the balance between generation and demand. However, high penetration of renewable energy such as photovoltaic and wind energy to the power grid requires a flexible control technique to maintain the stability of the power system. This paper presents an adaptive proportional-integral (PI) based genetic algorithm (GA) controller for a two-area non-reheat thermal plant coupled with renewable energy sources (RES). The test system is simulated in a MATLAB/Simulink environment. Test results of the proposed technique shows an improved performance with zero frequency deviation and less settling time after a load disturbance. PI based particle swarm optimization control is used as a benchmark.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126149728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karobia Pauline N., Ngoo Livingstone, Muriuki James
{"title":"Embedded Power System Monitoring Of Illegal Power Connections In Kenyan Domestic Supply","authors":"Karobia Pauline N., Ngoo Livingstone, Muriuki James","doi":"10.1109/PowerAfrica49420.2020.9219799","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219799","url":null,"abstract":"Globally Technical Losses (TLs) and Non-Technical Losses (NTLs) are a significant challenge for power distribution systems. Mostly NTLs is caused by illegal power connection which can be as much as half of all the energy supplied in some countries. This implies that power generated may not meet the demand and therefore the power utilities are diverting to other types of power generation that are cheaper, reliable and cost effective. High demand for electric power that does not match the current power generated always leads to shortage thus increasing the cost per unit of electric energy consumed. This highly affects the economy of any nation. Most utility company experiences loss of revenue since illegally consumed power cannot be measured or billed. The difference between the total energy sent to the consumers and the sum of energy consumed by all the connected consumers can be determined, and the total amount of NTLs in the distribution line evaluated. Also, the high losses incurred are a burden to the legally connected consumers since it is factored out in their bills. The scenario of NTLs is not restricted to underdeveloped countries and the percentage varies depending with the connected electric users. The techniques used are illegal tap wiring and meter tampering through security seal violations. The existing system in Kenya does not identify the location where illegal connection has occurred. The suggested embedded system will remotely locate the users who attempts to tap power at the service head which is not billed. The system will communicate with the utility company immediately about the status of the affected connection via Global System Communication. This will protect the distribution network in Kenya from high NTLs caused by illegal connections thus lowering the cost of electricity.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128777031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Non-Technical Power Loss Reduction and Transients Stability: Optimal Placement of Reclosers","authors":"W. O. Amolo, P. Musau, A. Nyete","doi":"10.1109/PowerAfrica49420.2020.9219824","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219824","url":null,"abstract":"Rarely do power distribution system, nowadays operates without a novel protection device to manage transients caused by electricity theft. Reliability requirements had been previously the subject, considered by researchers using reclosers to manage transients. However, Non-technical power loss and its cost reduction has not been sufficiently addressed to enhance high quality power supply. Consequently, consumers have always paid more on system losses. To safeguard on this menace, optimal reclosing, ENS.COST, firefly algorithm based has been discussed in this work. The results and analysis of proposed method had a forty three percent (43%) cost reduction on energy not served (ENS) during transient. Radial distribution system employed to analyze this can be replaced by a closed network for further work together with another novel optimization method other than Firefly algorithm for validation.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127697985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stephen Anokye, Elvis Twumasi, E. Frimpong, Bernice Monney Agyirakwa, Rhoda Etornam Kudor
{"title":"Intelligent Energy Management Device for Energy Conservation in Air conditioners","authors":"Stephen Anokye, Elvis Twumasi, E. Frimpong, Bernice Monney Agyirakwa, Rhoda Etornam Kudor","doi":"10.1109/PowerAfrica49420.2020.9219800","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219800","url":null,"abstract":"The paper reports on the design, construction, and pilot implementation of an intelligent controller for Airconditioners (ACs), to conserve energy. The intelligent controller is named Airro. Airro employs a pyroelectric infrared (PIR) sensor and a microcontroller to detect occupancy and determine whether the controlled AC should be turned off or on. A mobile application has also been developed to enable remote monitoring of the state of the AC and to control its operation. The device has been successfully piloted. Efforts are underway to roll it out at the Kwame Nkrumah University of Science and Technology (KNUST).","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122701969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Adaptive Distance Protection Scheme for High Varying Fault Resistances","authors":"Uma Uzubi, A. Ekwue, E. Ejiogu","doi":"10.1109/PowerAfrica49420.2020.9219863","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219863","url":null,"abstract":"The variation of fault resistances introduces error in the measured apparent impedance of the conventional distance protection scheme. With this, the measured apparent impedance at the relay location is not proportional to its length. This paper presents an adaptive protection scheme using Artificial Neural Network (ANN) to address the problem. A MATLAB based adaptive distance relaying scheme is proposed using the ANN feed-forward nonlinear supervised back-propagation algorithm based on the Levenberg-Marquardt network topology. The PSCAD /EMTDC software is used to generate the current and voltage signals for specified transmission lines which are used for subsequent ANN training and testing of the proposed algorithm. The proposed non-conventional adaptive scheme was validated with a new set of high fault resistances data using the proposed model. The results show the ability of ANN to correctly detect, classify and localized fault under varying fault resistance.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122722402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, Nana Twum Duah, E. Frimpong
{"title":"Policy Review of Impact of Distributed Generation on Power Quality","authors":"Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, Nana Twum Duah, E. Frimpong","doi":"10.1109/PowerAfrica49420.2020.9219986","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219986","url":null,"abstract":"Distributed Generation is employed to enhance power stability. However, large integration of DGs can have adverse effect on power quality (PQ) such as voltage stability and harmonic pollution. Thus, jeopardizing the grid stability. Policies such as IEEE 1547 and 519 grid code standards (std) have been formulated to regulate and harmonize DG operations. Whilst IEEE std 1547 forbid DGs to partake in voltage regulation, IEEE 519 on the other hand limits the current drawn to a total demand distortion (TDD) not exceeding 5%. This policy will inevitably result in voltage instability and harmonic contamination if the DG power output surges. Although these policies help to mitigate the negative impact of DGs, there is no single solution that is most appropriate for a particular jurisdiction in addressing them. Therefore, to secure the future of the electric grid, there is a need to revisit the grid codes standards regulating DG operation.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115337018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wavelet Analysis and Neural Network Scheme for Predicting Transient Stability Status","authors":"E. Frimpong, P. Okyere, J. Asumadu","doi":"10.1109/PowerAfrica49420.2020.9219977","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219977","url":null,"abstract":"This paper presents a method based on wavelet analysis (WA) and Multilayer perceptron neural network (MLPNN) to predict transient stability status (TSS) after a disturbance. It uses as input data, generator terminal frequency deviations extracted at a rate of thirty-two samples per cycle. Only the first eight frequency deviation samples per machine are needed. The eight samples are sub-divided into two sets, one set consisting of the first four samples and the other set consisting of the last four samples. Each set of samples is decomposed into 2 levels using the Daubechies 8 mother wavelet and the absolute peak value of detail coefficients obtained. The absolute peaks of detail coefficients of the first sample sets of all generators are added and so are the absolute peaks of detail coefficients of the second sample sets. The two summed values are then used as inputs to a trained MLPNN which predicts the TSS. The method was evaluated using the New England test system. It was noted to be 94.1% accurate.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115750726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Renewable Distributed Generations' Uncertainty Modelling: A Survey","authors":"O. A. Ajeigbe, J. Munda, Y. Hamam","doi":"10.1109/PowerAfrica49420.2020.9219893","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219893","url":null,"abstract":"Renewable energy distributed generation is reaching an unprecedented level of integration into power generation systems due to its numerous advantages. However, its increased penetration compounds the level of uncertainties being coped with in distribution systems. This aggravates the difficulty in making decisions in the context of large-scale penetration of renewable distributed generations, especially with the intermittent ones. Consequently, the analysis of uncertainty and modelling of the related system parameters is essential. This paper aims to provide a state-of-the-art review on uncertainty modelling approaches for distribution system studies and applications. This work focuses mainly on classifying and comparing the uncertainty modelling approaches and methodologies, presenting mathematical syntax of the methods, as well as the merits and demerits of the modelling methods. This study serves as the knowledge warehouse and selection tool for choosing the most suitable method for various applications.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130646165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lukman Adewale Ajao, J. Agajo, Buhari U. Umar, Tope Tobi Agboade, M. Adegboye
{"title":"Modeling and Implementation of Smart Home and Self-control Window using FPGA and Petri Net","authors":"Lukman Adewale Ajao, J. Agajo, Buhari U. Umar, Tope Tobi Agboade, M. Adegboye","doi":"10.1109/PowerAfrica49420.2020.9219925","DOIUrl":"https://doi.org/10.1109/PowerAfrica49420.2020.9219925","url":null,"abstract":"The function of the window is to provide comfort for the householders by regulating the indoor environment. However, most of the residence windows are still controlled manually. Although, a quite number of automated windows based on the Internet of Things (IoT) has been proposed in the literature, yet a smart windows control with multi-objectives functions related to the environmental factors remain open gap. This paper aims to contribute to this area by developing a cyber-physical system (CPS) for smart room and windows automation control (SRWAC) using set of rules generated from the Petri Net simulator for determining the system response to the inputs data sensed from the indoor and outdoor sensing units (temperature, dust, rain, and carbon monoxide sensors) in coding Atmega 328 controller. We also simulate the window controller using Field Programmable Gate Array (FPGA) in Xilinx ISE. The results of the system tested show that automated response of the indoor and outdoor conditions can be achieved spontaneously.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127045871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}